A Survey on Models and Query Languages for Temporally Annotated RDF
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2012, Vol 3, Issue 9
Abstract
In this paper, we provide a survey on the models and query languages for temporally annotated RDF. In most of the works, a temporally annotated RDF ontology is essentially a set of RDF triples associated with temporal constraints, where, in the simplest case, a temporal constraint is a validity temporal interval. However, a temporally annotated RDF ontology may also be a set of triples connecting resources with a specific lifespan, where each of these triples is also associated with a validity temporal interval. Further, a temporal RDF ontology may be a set of triples connecting resources as they stand at specific time points. Several query languages for temporally annotated RDF have been proposed, where most of which extend SPARQL or translate to SPARQL. Some of the works provide experimental results while the rest are purely theoretical.
Authors and Affiliations
Anastasia Analyti, Ioannis Pachoulakis
Keywords
Related Articles
- EP ID EP161259
- DOI -
- Views 97
- Downloads 0
New Approach of Automatic Modulation Classification based on in Phase-Quadrature Diagram Combined with Artificial Neural Network
Automatic Modulation Classification (AMC) with intelligent system is an attracting area of research due to the development of SDR (Software Defined Radio). This paper proposes a new algorithm based on a combination of k-...
Contributions to the Analysis and the Supervision of a Thermal Power Plant
Supervision systems play an important role in industry mainly due to the increasing demand for product quality and high efficiency, and to the growing integration of automatic control systems in technical processes. In f...
Early Development of UVM based Verification Environment of Image Signal Processing Designs using TLM Reference Model of RTL
With semiconductor industry trend of “smaller the better”, from an idea to a final product, more innovation on product portfolio and yet remaining competitive and profitable are few criteria which are culminating into pr...
Convolutional Neural Network Hyper-Parameters Optimization based on Genetic Algorithms
In machine learning for computer vision based applications, Convolutional Neural Network (CNN) is the most widely used technique for image classification. Despite these deep neural networks efficiency, choosing their opt...
Empirical Evaluation of Social and Traditional Search Tools for Adhoc Information Retrieval
The nature of World Wide Web (www) has evolved over the passage of time. Easier and faster availability of Internet has given rise to huge volumes of data available online. Another cause of huge volumes of data is the em...